Distance Prediction based on Handoff Strategy using Machine Learning

Day by day the importance of net and wireless technologies has been hugely will increase. The various wireless technologies square measure along to produce the consistent property to the users. Once the user moves from the vary of 1 wireless space network to a different wireless space network football play can get happens. Handoff may be a vital of wireless mobile communication. The football play algorithms offer gain, quality of signal (QOS). The 2 major issues square measure arising in football play, supernumerary incidence of football play and football play failure. To avert these problems, associate rule has to be enforced to attenuate the supernumerary football plays and handoff failures. Movement distance prediction primarily based rule presents during this paper that minimizes the supernumerary football plays and handoff failures once the mobile terminal senses the network of any wireless technology. This rule minimizes the supernumerary football play and failures of football play whenever prognostic movement distance in Wi-Fi (Wireless-Fidelity) cell smaller than the brink worth. Theoretical and simulation analysis of the rule shows that, movement distance prediction primarily based rule minimizes the chance of the incidence of supernumerary football play.